In tomography, measurements are taken through multiple views of a subject (e.g., human or animal in biomedical applications), and mathematical algorithms are used to convert these measurements into three-dimensional (3-D) images of the subject. Generally, in positron emission tomography (PET) and similar imaging methods, radioactive isotopes are injected into a subject. Decay of the isotopes (that is, a positron-electron annihilation event) results in photons being emitted from inside the animal.
In conventional PET, detectors positioned outside the animal detect emitted photon pairs when they hit the detectors. These interactions are recorded, including the particular detectors that are hit (the detection location) and the energy. Based on these recorded interactions, an image of where the radioactive isotope is distributed in the body can be imaged using a tomography image reconstruction algorithm.
Conventionally, emitted photon pairs from a source that are detected in coincidence by the detectors are used to reconstruct a 3-D tomographic image. True coincidence events are assumed to have occurred somewhere along the line between two photons detected within a preset coincidence time window. Thus, a line can be determined between the photon pair based on the location of the detected photos, and the determined lines are used to reconstruct the image using the tomography image reconstruction algorithm.
However, when a photon is scattered in tissue, such as in a Compton interaction, a scatter event occurs. Even when only one of the photons in a photon pair is scattered, producing so-called single scatter coincidence photons, the position of the annihilation event cannot be correctly localized. Thus, conventionally, the single scatter coincidence events are rejected using various techniques. For human patients, the scatter fraction is typically 50% of more of the coincidence events, resulting in the loss of significant amounts of information.